Analytics, Finance & Strategy
Senior individual contributor on Anthropic's Finance Analytics team, owning measurement of AI model value, market position, benchmarks, pricing elasticity, and launch analytics to inform executive decisions on pricing, packaging, and strategy. Requires hands-on SQL/Python, shaping ambiguous problems, and executive storytelling.
About the job
Key Responsibilities
- Build the relative-value measurement system: evolve our cross-product benchmark into a durable, trusted read on model and product value, spanning coding, agentic, and product-shaped tasks
- Inform pricing and packaging: construct task-cost approximations and price-elasticity estimates across differently priced products, and carry them into decisions
- Own launch and market analytics: run analytics around model launches, including capability-based revenue analyses and views of the broader market
- Deepen our market understanding: evaluate and integrate external datasets and research to strengthen our read on the market and how it's evolving
- Partner with Product Finance: take open-ended pricing, packaging, and positioning questions from vague ask to decision-grade answer
- Raise the bar: land narratives in executive forums and uplevel the team’s product-finance analytics practice by example
Minimum Qualifications
- Put shape around ambiguity: you’ve personally defined the measurement approach for questions nobody knew how to answer, without waiting for a fully specified ask
- Land narratives with executives: your analyses have changed pricing, product, or competitive decisions, and you can simplify for senior leaders without losing rigor
- Stay hands-on at senior scope: you still write the SQL and Python yourself, and you’d rather ship a defensible v1 with honest error bars than wait for perfect data
- Are inherently curious: you go one level deeper than asked and are energized by how fast models, products, and the market are moving
- Thrive amid shifting priorities: you juggle multiple fast-moving workstreams and stay effective when the plan changes weekly
- Work fluently with modern tooling: you’re strong at data visualization, use Claude and AI tools as force multipliers in analysis and BI, and can self-serve your own workflows across SQL, Python, dbt, and a cloud warehouse
Preferred Qualifications
- Experience designing evals or benchmarks for AI models or products
- Pricing and packaging analytics at scale, including elasticity estimation
- Market share estimation from imperfect third-party, panel, or survey data
- Fluency in the LLM model and product landscape
- Dimensional modeling and warehouse design experience (grain, SCDs, point-in-time correctness)
- Cloud platform experience (AWS, GCP) with orchestration, CI/CD for data, and testing/observability
Compensation & Benefits
- Annual Salary: $270,000—$320,000 USD
- Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
- Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Skills
SQL, Python, dbt, Data Visualization, AWS, GCP, Dimensional Modeling, Benchmarks, Price Elasticity, Market Analysis
Similar jobs
Data Science jobs
OpenAI
New York, NYThis senior data scientist will define measurement frameworks for AI-agent security, evaluate controls and security findings, and improve detection and response outcomes. The role requires 5+ years of quantitative experience, strong SQL and Python skills, and experience with cybersecurity or other adversarial-risk domains.
OpenAI
San Francisco, CAThe Data Scientist will shape analytics strategy and deliver forecasting, experimentation, optimization, dashboards, models, and decision tools for Real Estate & Workplace operations. The role requires strong applied statistics, causal inference, SQL, Python, stakeholder communication, and comfort working with ambiguous operational data.
OpenAI
San Francisco, CAPeople Data Scientist focused on AI fairness and bias testing for People systems. Designs algorithmic audits, validation studies, and fairness infrastructure across the employee lifecycle. Requires deep expertise in fairness metrics, statistical modeling, and Python/R/SQL.
Watershed
San Francisco, CA
Develops scientifically rigorous sustainability methodologies that become product capabilities for corporate climate and ESG data. The role combines climate expertise, GHG accounting, standards interpretation, data reasoning, and hands-on collaboration with engineers and product teams.
Plaid
San Francisco, CASenior Data Scientist supporting Plaid’s Credit product area, translating ambiguous product questions into analytics, metrics, experiments, and strategic insights. The role partners closely with product and engineering teams and requires 5+ years of data science or related analytics experience.